Wideband Channelization for Software-Defined Radio via Mobile Graphics Processors

Abstract—Wideband channelization is a computationally in-tensive task within software-defined radio (SDR). To support this task, the underlying hardware should provide high performance and allow flexible implementations. Traditional solutions use field-programmable gate arrays (FPGAs) to satisfy these require-ments. While FPGAs allow for flexible implementations, realiz-ing a FPGA implementation is a difficult and time-consuming process. On the other hand, multicore processors while more programmable, fail to satisfy performance requirements. Graph-ics processing units (GPUs) overcome the above limitations. However, traditional GPUs are power-hungry and can consume as much as 350 watts, making them ill-suited for many SDR environments, particularly those that are battery-powered. Here we explore the viability of low-power mobile graphics processors to simultaneously overcome the limitations of per-formance, flexibility, and power. Via execution profiling and performance analysis, we identify major bottlenecks in mapping the wideband channelization algorithm onto these devices and adopt several optimization techniques to achieve multiplicative speed-up over a multithreaded implementation. Overall, our approach delivers a speedup of up to 43-fold on the discrete AMD Radeon HD 6470M GPU and 27-fold on the integrated AMD Radeon HD 6480G GPU, when compared to a vectorized and multithreaded version running on the AMD A4-3300M CPU. Index Terms—polyphase filter banks; mobile GPU; wideband channelization; software-defined radio I